The present invention relates to artificial intelligence and more particularly to a method and apparatus for estimating body fat percentage of a person
With the steady increase in worldwide rates of obesity, the National Institutes of Health (NIH) and the World Health Organization (WHO) have recently adopted similar body weight standards for diagnosing overweightness and obesity. For example, a person is considered overweight according to these standards if the person""s body weight adjusted for height, referred to a body weight index (BMI=weight/height2), is greater than 25 kg/m2 and obese if the BMI is greater than 30 kg/m2. Conversely, being underweight is defined as having a BMI less than 18.5 kg/m2. Practitioners have been using these body weight guidelines in diagnosing the presence of excessive adiposity and prescribing treatment for their overweight patients.
Lately, there has been increasing interest in quantifying a person""s total body fat or the person""s body fat percentage rather than BMI as a direct measure of obesity. The main assumption of the BMI standards is that body mass, adjusted for stature, is associated with body fatness and consequent morbidity and mortality. However, there some individuals who are overweight according to the BMI standards, but not overfat (e.g. body builders), Similarly, there are some lean individuals such as marathon runners who are not xe2x80x9cunderweightxe2x80x9d in accordance with the BMI standards but who have a very low body fat content Due to the variations among the population, there is at present no accepted consensus on how BMI and body fat are linked.
Accordingly, several approaches have been developed for measuring body fat, but all of these approaches require special equipment. For example, am underwater or hydrostatic weighing technique compares a person""s weight in air and the person""s weight in water and, taking the person""s lung volume into account, computes the person""s body volume and density The body fat percentage is then estimated from the calculated body density. This technique, however, requires special equipment for weighing a person .underwater such as stainless steel water tanks.
Another body fat measurement technique is known as xe2x80x9cdual energy X-ray absorptiometryxe2x80x9d (DXA), in which a person is irradiated with X-rays to measure the bone mineral content and body fat percentage by differences in the X-ray absorption rates. This technique, too, requires special equipment to produce and measure the X-rays. Still another technique includes drinking heavy water comprising D2O or 3H2O and calculating the deuterium or tritium dilution to determine the total body water, from which the body fat percentage can be estimated. This approach require special ingredients, equipment, and expertise.
Bioelectronic impedance analysis (BIA) can also be used to estimate body fat percentage from measuring the electrical impedance of a person and correlating the impedance with the person""s standing height and body weight In contrast with the previous techniques, the BIA can be performed with relatively inexpensive pieces of equipment.
In all of these techniques, however, some additional equipment is required, ranging from the X-ray machines to bioelectronic impedance measurement devices. here is a need for a method and apparatus for estimating the body fat percentage, which is simple to apply and does not require special equipment or expertise. In fact, there is a need for a technique that can be performed over the Internet without requiring the user to purchase special equipment.
These and other needs are addressed by the present invention in which the body fat percentage for a person is estimated from the BMI of the person. The present invention stems from the discovery that the models for body fat percentage can be developed using a multiple regression analysis with the reciprocal of the BMI (1/BMI) as the independent variable. Use of the 1/BMI terms advantageously linearizes the data and avoids the need for logarithmic conversion or inclusion of power terms and therefore simplifies the computing apparatus and programs. Preferably, other potentially independent and easily obtained variables such as age, sex, and ethnicity are also used to provide precise estimates of the body fat percentage. All of such variables can readily be determined without the use of special equipment or expertise.
One aspect of the invention relates to an apparatus, a machine-implemented method, and software for estimating a body fat percentage of a person put indicating data concerning the person is received, and the body fat percentage of the person is then estimated based on a reciprocal of a body mass index (BMI), which is the quotient of the weight of the person divided by the square of the height of the person. Then the estimated body fat percentage is output to the user, Various embodiments of the apparatus include a body fat calculator, a personal computer programmed to estimate body fat percentage, a web server that provides a web site for estimating body fat percentages, and a scale that is equipped to weigh a person and use the measured weight to estimate the body fat percentage.
Still other objects and advantages of the present invention will become readily apparent from the following detailed description, simply by way of illustration of the best mode contemplated of carrying out the invention. As will be realized, the invention is capable of other and different embodiments, and its several details are capable of modifications in various obvious respects, all without departing from the invention. Accordingly, the drawing and description are to be regarded as illustrative in nature, and not as restrictive.